Please use this identifier to cite or link to this item:
https://doi.org/10.1080/03052150211748
DC Field | Value | |
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dc.title | A technique to achieve maximal manufacturing yield in engineering design | |
dc.contributor.author | Jayaram, J.S.R. | |
dc.contributor.author | Ibrahim, Y. | |
dc.contributor.author | Loh, H.T. | |
dc.contributor.author | Brombacher, A.C. | |
dc.date.accessioned | 2014-04-24T07:19:23Z | |
dc.date.available | 2014-04-24T07:19:23Z | |
dc.date.issued | 2002-05 | |
dc.identifier.citation | Jayaram, J.S.R., Ibrahim, Y., Loh, H.T., Brombacher, A.C. (2002-05). A technique to achieve maximal manufacturing yield in engineering design. Engineering Optimization 34 (3) : 279-305. ScholarBank@NUS Repository. https://doi.org/10.1080/03052150211748 | |
dc.identifier.issn | 0305215X | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/50855 | |
dc.description.abstract | Techniques to maximize manufacturing yield of an engineering design for mass manufactured products are well established. These techniques may be broadly grouped into geometrical and statistical techniques. The geometrical techniques suffer from the curse of dimensionality and therefore become very expensive when applied to problems with a large number of design parameters. The statistical techniques focus very much on optimizing the manufacturing yield through Monte Carlo simulations and always require a feasible starting solution to begin functioning. These could again be expensive in application. This paper seeks to address the maximization of the manufacturing yield. In doing so, it attempts to reduce the costs associated with the optimization. It also seeks to offer a technique which can begin the search with an infeasible solution and yet identify a maximal manufacturing yield region. The proposed technique is applied to a set of design problems. The results indicate that the proposed technique is capable of identifying regions of maximal manufacturing yield. | |
dc.description.uri | http://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1080/03052150211748 | |
dc.source | Scopus | |
dc.subject | Mass manufacturing | |
dc.subject | Optimization | |
dc.subject | Search strategy | |
dc.subject | Statistical techniques | |
dc.subject | Yield | |
dc.type | Article | |
dc.contributor.department | ELECTRICAL & COMPUTER ENGINEERING | |
dc.contributor.department | INDUSTRIAL & SYSTEMS ENGINEERING | |
dc.contributor.department | MECHANICAL ENGINEERING | |
dc.description.doi | 10.1080/03052150211748 | |
dc.description.sourcetitle | Engineering Optimization | |
dc.description.volume | 34 | |
dc.description.issue | 3 | |
dc.description.page | 279-305 | |
dc.description.coden | EGOPA | |
dc.identifier.isiut | 000175961000005 | |
Appears in Collections: | Staff Publications |
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